{"id":"W3197916540","doi":"10.1167/jov.21.9.2991","title":"Using Biological Motion to Perceive Human Movement During a Remote Task","year":2021,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Biological motion; Perception; Motion (physics); Task (project management); Movement (music); Computer science; Point (geometry); Computer vision; Human–computer interaction; Artificial intelligence; Cognitive psychology; Communication; Psychology; Acoustics; Neuroscience; Engineering; Mathematics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001580953,0.0002043138,0.0001057863,0.000196781,0.0001041842,0.0002485117,0.00009626374,0.0002540774,0.00141946],"category_scores_gemma":[0.001293345,0.0001046577,0.00008340858,0.00006822005,0.0001683857,0.000277712,0.0002832202,0.0001993248,0.0002331338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000812346,"about_ca_system_score_gemma":0.0001043585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008566582,"about_ca_topic_score_gemma":0.001526888,"domain_scores_codex":[0.9999278,0.00001910183,0.00000303248,0.00002462878,0.00001381581,0.00001170918],"domain_scores_gemma":[0.9998183,0.0000721958,0.00004098239,0.0000115537,0.00002549202,0.00003144597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006556504,0.0000741331,0.03215921,0.0001470689,0.00003670439,0.0001359167,0.0008877859,0.001015242,0.9148422,0.0002454669,0.0002834758,0.04951718],"study_design_scores_gemma":[0.00006247125,0.001993757,0.9048054,0.00008405023,0.00009399177,0.0008875243,0.001535058,0.02617804,0.06114555,0.0007473604,0.002395825,0.00007096197],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987018,0.0002329827,0.01042579,0.00005602804,0.00001687713,0.00003627869,0.0001255168,0.00004748489,0.002041074],"genre_scores_gemma":[0.9940859,0.0001066556,0.005200214,0.0000366719,0.000005846238,0.00001565673,0.00006938566,0.00000686998,0.0004727214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00141946,"threshold_uncertainty_score":0.004748523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06184173355628216,"score_gpt":0.3756094607890947,"score_spread":0.3137677272328125,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}